{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "d44e3c9b",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import time\n",
    "from tqdm import tqdm  # tqdm是显示循环进度条的库"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "a666e5ac",
   "metadata": {},
   "outputs": [],
   "source": [
    "class CliffWalkingEnv:\n",
    "    def __init__(self, ncol, nrow):\n",
    "        self.nrow = nrow\n",
    "        self.ncol = ncol\n",
    "        # 记录当前智能体位置的横坐标\n",
    "        self.x = 0\n",
    "        # 记录当前智能体位置的纵坐标\n",
    "        self.y = self.nrow - 1\n",
    "    \n",
    "    # 外部调用这个函数来改变当前位置 \n",
    "    def step(self, action):\n",
    "        # 4种动作, change[0]:上, change[1]:下, change[2]:左, change[3]:右。坐标系原点(0,0)定义在左上角\n",
    "        change = [[0, -1], [0, 1], [-1, 0], [1, 0]]\n",
    "        self.x = min(self.ncol - 1, max(0, self.x + change[action][0]))\n",
    "        self.y = min(self.nrow - 1, max(0, self.y + change[action][1]))\n",
    "        next_state = self.y * self.ncol + self.x\n",
    "        reward = -1\n",
    "        done = False\n",
    "        # 下一个位置在悬崖或者目标\n",
    "        if self.y == self.nrow - 1 and self.x > 0:\n",
    "            done = True\n",
    "            if self.x != self.ncol - 1:\n",
    "                reward = -100\n",
    "        return next_state, reward, done\n",
    "    \n",
    "    # 回归初始状态,坐标轴原点在左上角\n",
    "    def reset(self):\n",
    "        self.x = 0\n",
    "        self.y = self.nrow - 1\n",
    "        return self.y * self.ncol + self.x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "8545b159",
   "metadata": {},
   "outputs": [],
   "source": [
    "def reverse_calculate(n, col):\n",
    "    y = n // col\n",
    "    x = n % col\n",
    "    return x, y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "8b1b8050",
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_values(V):\n",
    "    # 重装V\n",
    "    V = np.reshape(V, (4, 12))\n",
    "    # 绘图\n",
    "    fig = plt.figure(figsize=(15, 5))\n",
    "    ax = fig.add_subplot(111)\n",
    "    im = ax.imshow(V, cmap='cool')\n",
    "    for (j, i), label in np.ndenumerate(V):\n",
    "        ax.text(i, j, np.round(label, 3), ha='center', va='center', fontsize=14)\n",
    "    plt.tick_params(bottom='off', left='off', labelbottom='off', labelleft='off')\n",
    "    plt.title('Optimal State Value Function')\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "fcf5c6e4",
   "metadata": {},
   "outputs": [],
   "source": [
    "class Sarsa:\n",
    "    def __init__(self, ncol, nrow, epsilon, alpha, gamma, n_action=4):\n",
    "        # 初始化Q(s,a)表格\n",
    "        self.Q_table = np.zeros([nrow * ncol, n_action])\n",
    "        # 动作个数\n",
    "        self.n_action = n_action\n",
    "        # 学习率\n",
    "        self.alpha = alpha\n",
    "        # 折扣因子\n",
    "        self.gamma = gamma\n",
    "        # epsilon-贪婪策略中的参数\n",
    "        self.epsilon = epsilon\n",
    "\n",
    "    # 选取下一步的操作,具体实现为epsilon-贪婪\n",
    "    def take_action(self, state):\n",
    "        if np.random.random() < self.epsilon:\n",
    "            action = np.random.randint(self.n_action)\n",
    "        else:\n",
    "            action = np.argmax(self.Q_table[state])\n",
    "        return action\n",
    "\n",
    "    # 用于打印策略\n",
    "    def best_action(self, state):\n",
    "        Q_max = np.max(self.Q_table[state])\n",
    "        a = [0 for _ in range(self.n_action)]\n",
    "        # 若两个动作的价值一样,都会记录下来\n",
    "        for i in range(self.n_action):\n",
    "            if self.Q_table[state, i] == Q_max:\n",
    "                a[i] = 1\n",
    "        return a\n",
    "    \n",
    "    def update(self, s0, a0, r, s1, a1):\n",
    "        td_error = r + self.gamma * self.Q_table[s1, a1] - self.Q_table[s0, a0]\n",
    "        self.Q_table[s0, a0] += self.alpha * td_error"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "275d3b3c",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Iteration 0: 100%|██████████| 50/50 [00:00<00:00, 1581.71it/s, episode=50, return=-119.400]\n",
      "Iteration 1: 100%|██████████| 50/50 [00:00<00:00, 1707.83it/s, episode=100, return=-63.000]\n",
      "Iteration 2: 100%|██████████| 50/50 [00:00<00:00, 1884.74it/s, episode=150, return=-51.200]\n",
      "Iteration 3: 100%|██████████| 50/50 [00:00<00:00, 2141.09it/s, episode=200, return=-48.100]\n",
      "Iteration 4: 100%|██████████| 50/50 [00:00<00:00, 1624.13it/s, episode=250, return=-35.700]\n",
      "Iteration 5: 100%|██████████| 50/50 [00:00<00:00, 2414.18it/s, episode=300, return=-29.900]\n",
      "Iteration 6: 100%|██████████| 50/50 [00:00<00:00, 2153.69it/s, episode=350, return=-28.300]\n",
      "Iteration 7: 100%|██████████| 50/50 [00:00<00:00, 2542.06it/s, episode=400, return=-27.700]\n",
      "Iteration 8: 100%|██████████| 50/50 [00:00<00:00, 2625.25it/s, episode=450, return=-28.500]\n",
      "Iteration 9: 100%|██████████| 50/50 [00:00<00:00, 2053.39it/s, episode=500, return=-18.900]\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ncol = 12\n",
    "nrow = 4\n",
    "env = CliffWalkingEnv(ncol, nrow)\n",
    "np.random.seed(0)\n",
    "epsilon = 0.1\n",
    "alpha = 0.1\n",
    "gamma = 0.9\n",
    "agent = Sarsa(ncol, nrow, epsilon, alpha, gamma)\n",
    "# 智能体在环境中运行的序列的数量\n",
    "num_episodes = 500\n",
    "\n",
    "# 记录每一条序列的回报\n",
    "return_list = []\n",
    "# 显示10个进度条\n",
    "# 外层循环 for i in range(10)：将整个训练过程分为 10 个阶段，每个阶段使用 tqdm 显示进度条。\n",
    "for i in range(10):\n",
    "    # tqdm的进度条功能\n",
    "    '''\n",
    "    这行代码中使用了 tqdm 库来创建一个进度条。tqdm 是一个快速、可扩展的 Python 进度条库，可以在循环中显示任务的进度。以下是对这行代码各部分的详细解释：\n",
    "        tqdm：这是库的名称，tqdm 来源于阿拉伯语中的 \"taqaddum\"，意思是 “进步”。它是一个用于在 Python 中创建和管理进度条的类。\n",
    "        total=int(num_episodes / 10)：这是 tqdm 类的一个参数，用于指定进度条的总步数。在这个例子中，num_episodes 是总的训练回合数，int(num_episodes / 10) 表示将总回合数分成 10 个部分，每个部分的步数作为当前进度条的总步数。\n",
    "        desc='Iteration %d' % i：这是另一个参数，用于设置进度条的描述信息。desc 是 \"description\" 的缩写。'Iteration %d' % i 是一个格式化字符串，i 是外层循环的迭代变量，每次循环时，i 的值会被插入到格式化字符串中，从而显示当前是第几次迭代。\n",
    "        as pbar：这是 Python 中 with 语句的一部分，用于将 tqdm 创建的进度条对象赋值给变量 pbar。通过这个变量，可以在后续的代码中更新进度条的状态，例如使用 pbar.update(1) 来增加进度条的步数。\n",
    "        with 语句：with 语句用于确保在代码块执行结束后，资源能够被正确地清理和释放。在这个例子中，当 with 代码块结束时，tqdm 进度条会自动关闭，并显示最终的进度信息。\n",
    "    '''\n",
    "    with tqdm(total=int(num_episodes / 10), desc='Iteration %d' % i) as pbar:\n",
    "        # 每个进度条的序列数\n",
    "        # 内层循环 for i_episode in range(int(num_episodes / 10))：每个阶段训练 num_episodes / 10 条序列。\n",
    "        for i_episode in range(int(num_episodes / 10)):\n",
    "            # episode_return = 0：初始化当前序列的回报为 0。\n",
    "            episode_return = 0\n",
    "            # state = env.reset()：重置环境，获取初始状态。\n",
    "            state = env.reset()\n",
    "            # action = agent.take_action(state)：智能体根据当前状态选择一个动作。\n",
    "            action = agent.take_action(state)\n",
    "            done = False\n",
    "            while not done:\n",
    "                '''\n",
    "                打印价值、动作函数\n",
    "                a_map = {0: '上', 1:'下', 2: '左', 3: '右'}\n",
    "                print(f'agent.Q_table[{state % env.ncol, state // env.ncol}]:', agent.Q_table[state], '动作：', a_map[action])\n",
    "                time.sleep(1)\n",
    "                \n",
    "                agent.Q_table[(0, 3)]: [0. 0. 0. 0.] 动作： 上\n",
    "                agent.Q_table[(0, 2)]: [0. 0. 0. 0.] 动作： 上\n",
    "                agent.Q_table[(0, 1)]: [0. 0. 0. 0.] 动作： 上\n",
    "                agent.Q_table[(0, 0)]: [0. 0. 0. 0.] 动作： 上\n",
    "                agent.Q_table[(0, 0)]: [-0.1  0.   0.   0. ] 动作： 上\n",
    "                agent.Q_table[(0, 0)]: [-0.19  0.    0.    0.  ] 动作： 下\n",
    "                agent.Q_table[(0, 1)]: [-0.1  0.   0.   0. ] 动作： 下\n",
    "                agent.Q_table[(0, 2)]: [-0.1  0.   0.   0. ] 动作： 下\n",
    "                agent.Q_table[(0, 3)]: [-0.1  0.   0.   0. ] 动作： 下\n",
    "                agent.Q_table[(0, 3)]: [-0.1 -0.1  0.   0. ] 动作： 下\n",
    "                agent.Q_table[(0, 3)]: [-0.1  -0.19  0.    0.  ] 动作： 右\n",
    "                agent.Q_table[(0, 3)]: [-0.1  -0.19 -0.1   0.  ] 动作： 右\n",
    "                agent.Q_table[(0, 3)]: [-0.1  -0.19 -0.19  0.  ] 动作： 右\n",
    "                随机探索\n",
    "                agent.Q_table[(0, 3)]: [ -0.1   -0.19  -0.19 -10.  ] 动作： 下\n",
    "                agent.Q_table[(0, 3)]: [ -0.1   -0.28  -0.19 -10.  ] 动作： 上\n",
    "                agent.Q_table[(0, 2)]: [-0.1 -0.1  0.   0. ] 动作： 右\n",
    "                agent.Q_table[(0, 2)]: [-0.1 -0.1 -0.1  0. ] 动作： 右\n",
    "                agent.Q_table[(0, 2)]: [-0.1  -0.1  -0.19  0.  ] 动作： 右\n",
    "                agent.Q_table[(1, 2)]: [0. 0. 0. 0.] 动作： 上\n",
    "                agent.Q_table[(1, 1)]: [0. 0. 0. 0.] 动作： 上\n",
    "                agent.Q_table[(1, 0)]: [0. 0. 0. 0.] 动作： 上\n",
    "                agent.Q_table[(1, 0)]: [-0.1  0.   0.   0. ] 动作： 上\n",
    "                '''\n",
    "\n",
    "                # next_state, reward, done = env.step(action)：执行动作，获取下一个状态、奖励和序列是否结束的标志。\n",
    "                next_state, reward, done = env.step(action)\n",
    "                # next_action = agent.take_action(next_state)：智能体根据下一个状态选择下一个动作。\n",
    "                next_action = agent.take_action(next_state)\n",
    "                # 累加当前序列的回报，这里回报的计算不进行折扣因子衰减\n",
    "                episode_return += reward\n",
    "                # 智能体根据当前状态、动作、奖励、下一个状态和下一个动作更新 Q 值。\n",
    "                agent.update(state, action, reward, next_state, next_action)\n",
    "                # 更新当前状态和动作。\n",
    "                state = next_state\n",
    "                action = next_action\n",
    "\n",
    "                # # 打印价值函数\n",
    "                # out = [np.max(agent.Q_table[key]) for key in range(48)]\n",
    "                # plot_values(out)\n",
    "                # time.sleep(1)\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "            # 将当前序列的回报添加到回报列表中。\n",
    "            return_list.append(episode_return)\n",
    "            # 每10条序列打印一下这10条序列的平均回报\n",
    "            if (i_episode + 1) % 10 == 0:\n",
    "                # 每 10 条序列打印一次这 10 条序列的平均回报。\n",
    "                pbar.set_postfix({\n",
    "                    'episode':\n",
    "                    '%d' % (num_episodes / 10 * i + i_episode + 1),\n",
    "                    'return':\n",
    "                    '%.3f' % np.mean(return_list[-10:])\n",
    "                })\n",
    "            # 更新进度条。\n",
    "            pbar.update(1)\n",
    "\n",
    "episodes_list = list(range(len(return_list)))\n",
    "plt.plot(episodes_list, return_list)\n",
    "plt.xlabel('Episodes')\n",
    "plt.ylabel('Returns')\n",
    "plt.title('Sarsa on {}'.format('Cliff Walking'))\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "92493eae",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Sarsa算法最终收敛得到的策略为：\n",
      "ooo> ooo> ooo> ooo> ooo> ooo> ooo> ooo> ooo> ooo> ooo> ovoo \n",
      "ooo> ooo> ooo> ooo> ooo> ooo> ooo> ooo> ooo> ooo> ooo> ovoo \n",
      "^ooo ooo> ^ooo ooo> ooo> ooo> ooo> ^ooo ^ooo ooo> ooo> ovoo \n",
      "^ooo **** **** **** **** **** **** **** **** **** **** EEEE \n"
     ]
    }
   ],
   "source": [
    "def print_agent(agent, env, action_meaning, disaster=[], end=[]):\n",
    "    for i in range(env.nrow):\n",
    "        for j in range(env.ncol):\n",
    "            if (i * env.ncol + j) in disaster:\n",
    "                print('****', end=' ')\n",
    "            elif (i * env.ncol + j) in end:\n",
    "                print('EEEE', end=' ')\n",
    "            else:\n",
    "                a = agent.best_action(i * env.ncol + j)\n",
    "                pi_str = ''\n",
    "                for k in range(len(action_meaning)):\n",
    "                    pi_str += action_meaning[k] if a[k] > 0 else 'o'\n",
    "                print(pi_str, end=' ')\n",
    "        print()\n",
    "\n",
    "\n",
    "action_meaning = ['^', 'v', '<', '>']\n",
    "print('Sarsa算法最终收敛得到的策略为：')\n",
    "print_agent(agent, env, action_meaning, list(range(37, 47)), [47])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "d8fc23b1",
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_values(V):\n",
    "    # 重装V\n",
    "    V = np.reshape(V, (4, 12))\n",
    "    # 绘图\n",
    "    fig = plt.figure(figsize=(15, 5))\n",
    "    ax = fig.add_subplot(111)\n",
    "    im = ax.imshow(V, cmap='cool')\n",
    "    for (j, i), label in np.ndenumerate(V):\n",
    "        ax.text(i, j, np.round(label, 3), ha='center', va='center', fontsize=14)\n",
    "    plt.tick_params(bottom='off', left='off', labelbottom='off', labelleft='off')\n",
    "    plt.title('Optimal State Value Function')\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "a3336af5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "out = [np.max(agent.Q_table[key]) for key in range(48)]\n",
    "plot_values(out)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "e43d3a73",
   "metadata": {},
   "outputs": [],
   "source": [
    "class nstep_Saras:\n",
    "    \"\"\" n步Sarsa算法 \"\"\"\n",
    "    def __init__(self, n, ncol, nrow, epsilon, alpha, gamma, n_action=4):\n",
    "        self.Q_table = np.zeros([nrow * ncol, n_action])\n",
    "        self.n_action = n_action\n",
    "        self.alpha = alpha\n",
    "        self.gamma = gamma\n",
    "        self.epsilon = epsilon\n",
    "        # 采用n步Sarsa算法\n",
    "        self.n = n\n",
    "        # 保存之前的状态\n",
    "        self.state_list = []\n",
    "        # 保存之前的动作\n",
    "        self.action_list = []\n",
    "        # 保存之前的奖励\n",
    "        self.reward_list = []\n",
    "    \n",
    "    def take_action(self, state):\n",
    "        if np.random.random() < self.epsilon:\n",
    "            action = np.random.randint(self.n_action)\n",
    "        else:\n",
    "            action = np.argmax(self.Q_table[state])\n",
    "        return action\n",
    "    \n",
    "    # 用于打印策略\n",
    "    def best_action(self, state):\n",
    "        Q_max = np.max(self.Q_table[state])\n",
    "        a = [0 for _ in range(self.n_action)]\n",
    "        for i in range(self.n_action):\n",
    "            if self.Q_table[state, i] == Q_max:\n",
    "                a[i] = 1\n",
    "        return a\n",
    "    \n",
    "    def update(self, s0, a0, r, s1, a1, done):\n",
    "        '''\n",
    "        更新前\n",
    "        self.state_list: [36, 24, 12, 0]\n",
    "        self.action_list: [np.int64(0), np.int64(0), np.int64(0), np.int64(0)]\n",
    "        self.reward_list: [-1, -1, -1, -1]\n",
    "        '''      \n",
    "        self.state_list.append(s0)\n",
    "        self.action_list.append(a0)\n",
    "        self.reward_list.append(r)\n",
    "        # 若保存的数据可以进行n步更新\n",
    "        if len(self.state_list) == self.n:\n",
    "            # 得到Q(s_{t+n}, a_{t+n}) \n",
    "            G = self.Q_table[s1, a1]\n",
    "            for i in reversed(range(self.n)):\n",
    "                # 不断向前计算每一步的回报\n",
    "                G = self.gamma * G + self.reward_list[i]\n",
    "                # 如果到达终止状态,最后几步虽然长度不够n步,也将其进行更新。\n",
    "                if done and i > 0:\n",
    "                    '''\n",
    "                    if -100 in self.reward_list:\n",
    "                        print(self.reward_list)\n",
    "                    elif 47 in self.state_list:\n",
    "                        print(\"终点：\")\n",
    "                        print(self.reward_list)\n",
    "                    [-1, -1, -1, -1, -100]\n",
    "                    [-1, -1, -1, -1, -100]\n",
    "                    [-1, -1, -1, -1, -100]\n",
    "                    [-1, -1, -1, -1, -100]\n",
    "                    '''\n",
    "                    '''\n",
    "                    假设当前处于序列的终止状态，已经积累了 3 步的信息（而n = 5），此时self.state_list、self.action_list \n",
    "                    和 self.reward_list 中分别存储了这 3 步的状态、动作和奖励。在反向计算累计回报G的过程中，当遇到终止状\n",
    "                    态（done = True）时，对于最后这 3 步中除最早那一步之外的状态 - 动作对，都会按照上述公式进行 Q 值更新。\n",
    "                    这样可以确保即使序列提前结束，也能充分利用已有的信息来更新 Q 表。\n",
    "                    '''\n",
    "                    s = self.state_list[i]\n",
    "                    a = self.action_list[i]\n",
    "                    self.Q_table[s, a] += self.alpha * (G - self.Q_table[s, a])\n",
    "            # 将需要更新的状态动作从列表中删除,下次不必更新\n",
    "            s = self.state_list.pop(0)\n",
    "            a = self.action_list.pop(0)\n",
    "            self.reward_list.pop(0)\n",
    "            # n步Sarsa的主要更新步骤\n",
    "            self.Q_table[s, a] += self.alpha * (G - self.Q_table[s, a])\n",
    "        # 如果到达终止状态,即将开始下一条序列,则将列表全清空\n",
    "        if done:\n",
    "            self.state_list = []\n",
    "            self.action_list = []\n",
    "            self.reward_list = []\n",
    "        '''         \n",
    "        更新后\n",
    "        self.state_list: [24, 12, 0, 0]\n",
    "        self.action_list: [np.int64(0), np.int64(0), np.int64(0), np.int64(0)]\n",
    "        self.reward_list: [-1, -1, -1, -1]\n",
    "        '''\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "081b45df",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Iteration 0: 100%|██████████| 50/50 [00:00<00:00, 1147.80it/s, {'spisode': '50', 'return': '-26.500'}]\n",
      "Iteration 1: 100%|██████████| 50/50 [00:00<00:00, 2352.23it/s, {'spisode': '100', 'return': '-35.200'}]\n",
      "Iteration 2: 100%|██████████| 50/50 [00:00<00:00, 2791.07it/s, {'spisode': '150', 'return': '-20.100'}]\n",
      "Iteration 3: 100%|██████████| 50/50 [00:00<00:00, 2997.60it/s, {'spisode': '200', 'return': '-27.200'}]\n",
      "Iteration 4: 100%|██████████| 50/50 [00:00<00:00, 2133.53it/s, {'spisode': '250', 'return': '-19.300'}]\n",
      "Iteration 5: 100%|██████████| 50/50 [00:00<00:00, 2494.35it/s, {'spisode': '300', 'return': '-27.400'}]\n",
      "Iteration 6: 100%|██████████| 50/50 [00:00<00:00, 2009.13it/s, {'spisode': '350', 'return': '-28.000'}]\n",
      "Iteration 7: 100%|██████████| 50/50 [00:00<00:00, 2290.99it/s, {'spisode': '400', 'return': '-36.500'}]\n",
      "Iteration 8: 100%|██████████| 50/50 [00:00<00:00, 2319.19it/s, {'spisode': '450', 'return': '-27.000'}]\n",
      "Iteration 9: 100%|██████████| 50/50 [00:00<00:00, 2139.27it/s, {'spisode': '500', 'return': '-19.100'}]\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "np.random.seed(0)\n",
    "# 5步Sarsa算法\n",
    "n_step = 5\n",
    "alpha = 0.1\n",
    "epsilon = 0.1\n",
    "gamma = 0.9\n",
    "agent = nstep_Saras(n_step, ncol, nrow, epsilon, alpha, gamma)\n",
    "# 智能体在环境中运行的序列的数量\n",
    "num_episodes = 500\n",
    "\n",
    "# 记录每一条序列的回报\n",
    "return_list = []\n",
    "# 显示10个进度条\n",
    "for i in range(10):\n",
    "    #tqdm的进度条功能\n",
    "    with tqdm(total=int(num_episodes / 10), desc='Iteration %d' % i) as pbar:\n",
    "        # 每个进度条的序列数\n",
    "        for i_episode in range(int(num_episodes / 10)):\n",
    "            episode_return = 0\n",
    "            state = env.reset()\n",
    "            \n",
    "            action = agent.take_action(state)\n",
    "            done = False\n",
    "            while not done:\n",
    "\n",
    "                '''\n",
    "                a_map = {0: '上', 1:'下', 2: '左', 3: '右'}\n",
    "                print(f'agent.Q_table[{state % env.ncol, state // env.ncol}]:', agent.Q_table[state], '动作：', a_map[action])\n",
    "                time.sleep(1)\n",
    "                \n",
    "                agent.Q_table[(0, 3)]: [0. 0. 0. 0.] 动作： 上\n",
    "                agent.Q_table[(0, 2)]: [0. 0. 0. 0.] 动作： 上\n",
    "                agent.Q_table[(0, 1)]: [0. 0. 0. 0.] 动作： 上\n",
    "                agent.Q_table[(0, 0)]: [0. 0. 0. 0.] 动作： 上\n",
    "                agent.Q_table[(0, 0)]: [0. 0. 0. 0.] 动作： 上\n",
    "                agent.Q_table[(0, 0)]: [0. 0. 0. 0.] 动作： 上\n",
    "                agent.Q_table[(0, 0)]: [0. 0. 0. 0.] 动作： 上\n",
    "                agent.Q_table[(0, 0)]: [0. 0. 0. 0.] 动作： 上\n",
    "                agent.Q_table[(0, 0)]: [-0.40951  0.       0.       0.     ] 动作： 上\n",
    "                agent.Q_table[(0, 0)]: [-0.778069  0.        0.        0.      ] 动作： 下\n",
    "                agent.Q_table[(0, 1)]: [-0.40951  0.       0.       0.     ] 动作： 下\n",
    "                agent.Q_table[(0, 2)]: [-0.40951  0.       0.       0.     ] 动作： 下\n",
    "                agent.Q_table[(0, 3)]: [-0.40951  0.       0.       0.     ] 动作： 下\n",
    "                agent.Q_table[(0, 3)]: [-0.40951  0.       0.       0.     ] 动作： 下\n",
    "                agent.Q_table[(0, 3)]: [-0.40951  0.       0.       0.     ] 动作： 下\n",
    "                agent.Q_table[(0, 3)]: [-0.40951  0.       0.       0.     ] 动作： 下\n",
    "                agent.Q_table[(0, 3)]: [-0.40951  0.       0.       0.     ] 动作： 下\n",
    "                agent.Q_table[(0, 3)]: [-0.40951 -0.40951  0.       0.     ] 动作： 下\n",
    "                agent.Q_table[(0, 3)]: [-0.40951  -0.778069  0.        0.      ] 动作： 右\n",
    "                agent.Q_table[(0, 3)]: [-0.40951   -1.1097721  0.         0.       ] 动作： 右\n",
    "                agent.Q_table[(0, 3)]: [-0.40951    -1.40830489  0.          0.        ] 动作： 右\n",
    "                agent.Q_table[(0, 3)]: [-0.40951   -1.6769844  0.         0.       ] 动作： 右\n",
    "                agent.Q_table[(0, 3)]: [-0.40951    -1.91879596  0.          0.        ] 动作： 右\n",
    "                agent.Q_table[(0, 3)]: [-0.40951    -1.91879596 -0.40951     0.        ] 动作： 右\n",
    "                agent.Q_table[(0, 3)]: [-0.40951    -1.91879596 -0.778069    0.        ] 动作： 右\n",
    "                agent.Q_table[(0, 3)]: [ -0.40951     -1.91879596 -27.56909107 -10.        ] 动作： 上\n",
    "                agent.Q_table[(0, 2)]: [-0.40951 -0.40951  0.       0.     ] 动作： 右\n",
    "                agent.Q_table[(0, 2)]: [-0.40951 -0.40951  0.       0.     ] 动作： 右\n",
    "                agent.Q_table[(0, 2)]: [-0.40951 -0.40951  0.       0.     ] 动作： 右\n",
    "                agent.Q_table[(0, 2)]: [-0.40951 -0.40951  0.       0.     ] 动作： 右\n",
    "                agent.Q_table[(0, 2)]: [-0.40951 -0.40951  0.       0.     ] 动作： 右\n",
    "                agent.Q_table[(0, 2)]: [-0.40951 -0.40951 -0.40951  0.     ] 动作： 右\n",
    "                agent.Q_table[(0, 2)]: [-0.40951  -0.40951  -0.778069  0.      ] 动作： 右\n",
    "                agent.Q_table[(1, 2)]: [0. 0. 0. 0.] 动作： 上\n",
    "                agent.Q_table[(1, 1)]: [0. 0. 0. 0.] 动作： 上\n",
    "                agent.Q_table[(1, 0)]: [0. 0. 0. 0.] 动作： 上\n",
    "                '''\n",
    "\n",
    "                next_state , reward, done = env.step(action)\n",
    "                next_action = agent.take_action(next_state)\n",
    "                # 这里回报的计算不进行折扣因子衰减\n",
    "                episode_return += reward\n",
    "                agent.update(state, action, reward, next_state, next_action, done)\n",
    "                state = next_state\n",
    "                action = next_action\n",
    "            return_list.append(episode_return)\n",
    "            # 每10条序列打印一下这10条序列的平均回报\n",
    "            if (i_episode + 1) % 10 == 0:\n",
    "                pbar.set_postfix_str({\n",
    "                    'spisode':\n",
    "                    '%d' % (num_episodes / 10 * i + i_episode + 1),\n",
    "                    'return':\n",
    "                    '%.3f' % np.mean(return_list[-10:])\n",
    "                })\n",
    "            pbar.update(1)\n",
    "\n",
    "episodes_list = list(range(len(return_list)))\n",
    "plt.plot(episodes_list, return_list)\n",
    "plt.xlabel('Episodes')\n",
    "plt.ylabel('Returns')\n",
    "plt.title('Sarsa on {}'.format('Cliff Walking'))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "a0d46dc4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "5步Sarsa算法最终收敛得到的策略为：\n",
      "ooo> ooo> ooo> ooo> ooo> ooo> ooo> ooo> ooo> ooo> ooo> ovoo \n",
      "^ooo ^ooo ^ooo oo<o ^ooo ^ooo ^ooo ^ooo ooo> ooo> ^ooo ovoo \n",
      "ooo> ^ooo ^ooo ^ooo ^ooo ^ooo ^ooo ooo> ooo> ^ooo ooo> ovoo \n",
      "^ooo **** **** **** **** **** **** **** **** **** **** EEEE \n"
     ]
    }
   ],
   "source": [
    "action_meaning = ['^', 'v', '<', '>']\n",
    "print('5步Sarsa算法最终收敛得到的策略为：')\n",
    "print_agent(agent, env, action_meaning, list(range(37, 47)), [47])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "9bf85e21",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "out = [np.max(agent.Q_table[key]) for key in range(48)]\n",
    "plot_values(out)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "b678ee19",
   "metadata": {},
   "outputs": [],
   "source": [
    "class QLearning:\n",
    "    \"\"\" Q-learning算法 \"\"\"\n",
    "    def __init__(self, ncol, nrow, epsilon, alpha, gamma, n_action=4):\n",
    "        # 初始化Q(s,a)表格\n",
    "        self.Q_table = np.zeros([nrow * ncol, n_action])\n",
    "        # 动作个数\n",
    "        self.n_action = n_action\n",
    "        # 学习率\n",
    "        self.alpha = alpha\n",
    "        # 折扣因子\n",
    "        self.gamma = gamma\n",
    "        # epsilon-贪婪策略中的参数\n",
    "        self.epsilon = epsilon\n",
    "\n",
    "    # 选取下一步的操作\n",
    "    def take_action(self, state):\n",
    "        if np.random.random() < self.epsilon:\n",
    "            action = np.random.randint(self.n_action)\n",
    "        else:\n",
    "            action = np.argmax(self.Q_table[state])\n",
    "        return action\n",
    "    \n",
    "    # 用于打印策略\n",
    "    def best_action(self, state):\n",
    "        Q_max = np.max(self.Q_table[state])\n",
    "        # a = [0 for _ in range(self.n_action)]\n",
    "        a = [0] * self.n_action\n",
    "        for i in range(self.n_action):\n",
    "            if self.Q_table[state, i] == Q_max:\n",
    "                a[i] = 1\n",
    "        return a\n",
    "    \n",
    "    def update(self, s0, a0, r, s1):\n",
    "        td_error = r + self.gamma * self.Q_table[s1].max() - self.Q_table[s0, a0]\n",
    "        self.Q_table[s0, a0] += self.alpha * td_error"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "84987246",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Iteration 0: 100%|██████████| 50/50 [00:00<00:00, 772.69it/s, episode=50, return=-105.700]\n",
      "Iteration 1: 100%|██████████| 50/50 [00:00<00:00, 760.44it/s, episode=100, return=-70.900]\n",
      "Iteration 2: 100%|██████████| 50/50 [00:00<00:00, 1432.86it/s, episode=150, return=-56.500]\n",
      "Iteration 3: 100%|██████████| 50/50 [00:00<00:00, 1444.86it/s, episode=200, return=-46.500]\n",
      "Iteration 4: 100%|██████████| 50/50 [00:00<00:00, 1175.58it/s, episode=250, return=-40.800]\n",
      "Iteration 5: 100%|██████████| 50/50 [00:00<00:00, 1016.11it/s, episode=300, return=-20.400]\n",
      "Iteration 6: 100%|██████████| 50/50 [00:00<00:00, 1375.26it/s, episode=350, return=-45.700]\n",
      "Iteration 7: 100%|██████████| 50/50 [00:00<00:00, 1544.15it/s, episode=400, return=-32.800]\n",
      "Iteration 8: 100%|██████████| 50/50 [00:00<00:00, 1857.61it/s, episode=450, return=-22.700]\n",
      "Iteration 9: 100%|██████████| 50/50 [00:00<00:00, 1594.39it/s, episode=500, return=-61.700]\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Q-learning算法最终收敛得到的策略为：\n",
      "^ooo ovoo ovoo ^ooo ^ooo ovoo ooo> ^ooo ^ooo ooo> ooo> ovoo \n",
      "ooo> ooo> ooo> ooo> ooo> ooo> ^ooo ooo> ooo> ooo> ooo> ovoo \n",
      "ooo> ooo> ooo> ooo> ooo> ooo> ooo> ooo> ooo> ooo> ooo> ovoo \n",
      "^ooo **** **** **** **** **** **** **** **** **** **** EEEE \n"
     ]
    }
   ],
   "source": [
    "np.random.seed(0)\n",
    "epsilon = 0.1\n",
    "alpha = 0.1\n",
    "gamma = 0.9\n",
    "agent = QLearning(ncol, nrow, epsilon, alpha, gamma)\n",
    "# 智能体在环境中运行的序列的数量\n",
    "num_episodes = 500\n",
    "\n",
    "# 记录每一条序列的回报\n",
    "return_list = [] \n",
    "# 显示10个进度条\n",
    "for i in range(10):\n",
    "    # tqdm的进度条功能\n",
    "    with tqdm(total=int(num_episodes / 10), desc='Iteration %d' % i) as pbar:\n",
    "        # 每个进度条的序列数\n",
    "        for i_episode in range(int(num_episodes / 10)):\n",
    "            episode_return = 0\n",
    "            state = env.reset()\n",
    "            done = False\n",
    "            while not done:\n",
    "                '''\n",
    "                a_map = {0: '上', 1:'下', 2: '左', 3: '右'}\n",
    "                print(f'agent.Q_table[{state % env.ncol, state // env.ncol}]:', agent.Q_table[state], '动作：', a_map[action])\n",
    "                time.sleep(1)\n",
    "                agent.Q_table[(0, 3)]: [0. 0. 0. 0.] 动作： 右\n",
    "                agent.Q_table[(0, 2)]: [0. 0. 0. 0.] 动作： 上\n",
    "                agent.Q_table[(0, 1)]: [0. 0. 0. 0.] 动作： 上\n",
    "                agent.Q_table[(0, 0)]: [0. 0. 0. 0.] 动作： 上\n",
    "                agent.Q_table[(0, 0)]: [-0.1  0.   0.   0. ] 动作： 上\n",
    "                agent.Q_table[(0, 1)]: [-0.1  0.   0.   0. ] 动作： 下\n",
    "                agent.Q_table[(0, 2)]: [-0.1  0.   0.   0. ] 动作： 下\n",
    "                agent.Q_table[(0, 3)]: [-0.1  0.   0.   0. ] 动作： 下\n",
    "                agent.Q_table[(0, 3)]: [-0.1 -0.1  0.   0. ] 动作： 下\n",
    "                agent.Q_table[(0, 3)]: [-0.1 -0.1 -0.1  0. ] 动作： 左\n",
    "                agent.Q_table[(0, 3)]: [ -0.1  -0.1  -0.1 -10. ] 动作： 右\n",
    "                agent.Q_table[(0, 2)]: [-0.1 -0.1  0.   0. ] 动作： 上\n",
    "                agent.Q_table[(0, 2)]: [-0.1 -0.1 -0.1  0. ] 动作： 左\n",
    "                agent.Q_table[(1, 2)]: [0. 0. 0. 0.] 动作： 右\n",
    "                agent.Q_table[(1, 1)]: [0. 0. 0. 0.] 动作： 上\n",
    "                agent.Q_table[(1, 2)]: [-0.1  0.   0.   0. ] 动作： 下\n",
    "                '''\n",
    "                action = agent.take_action(state)\n",
    "                next_state, reward, done = env.step(action)\n",
    "                # 这里回报的计算不进行折扣因子衰减\n",
    "                episode_return += reward\n",
    "                agent.update(state, action, reward, next_state)\n",
    "                state = next_state\n",
    "            return_list.append(episode_return)\n",
    "            # 每10条序列打印一下这10条序列的平均回报\n",
    "            if (i_episode + 1) % 10 == 0:\n",
    "                pbar.set_postfix({\n",
    "                    'episode':\n",
    "                    '%d' % (num_episodes / 10 * i + i_episode + 1),\n",
    "                    'return':\n",
    "                    '%.3f' % np.mean(return_list[-10:])\n",
    "                })\n",
    "            pbar.update(1)\n",
    "\n",
    "episodes_list = list(range(len(return_list)))\n",
    "plt.plot(episodes_list, return_list)\n",
    "plt.xlabel('Episodes')\n",
    "plt.ylabel('Returns')\n",
    "plt.title('Q-learning on Cliff Walking')\n",
    "plt.show()\n",
    "\n",
    "action_meaning = ['^', 'v', '<', '>']\n",
    "print('Q-learning算法最终收敛得到的策略为：')\n",
    "print_agent(agent, env, action_meaning, list(range(37, 47)), [47])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "482f4cf9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "out = [np.max(agent.Q_table[key]) for key in range(48)]\n",
    "plot_values(out)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": ".venv",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.11"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
